Billing Audit

WoundScribe's intelligence sits on both ends of a wound encounter: it verifies your intake before the AI drafts a note, and reviews the finished chart for rationale, billing, codes, and gaps before you sign. Here's how a diabetic foot ulcer encounter on Dorothy Hale's right heel moves from intake to a signed, audit-ready chart. 1. Verify intake. Open the wound and complete the required fields marked with an orange asterisk — Wound Name, Wound Type, and Wound Location. Miss one and the field turns red with a specific message. Add width and height or visit notes so the AI has something to analyze, and the Continue to AI Analysis button unlocks. 2. Run the agent chain. Summarizer, Assessment, and Planner draft the note in sequence. The Validator then returns a verdict — in this case, Conditionally Approved, with three concrete issues to address before signing. 3. Review the Encounter screen. The SOAP note sits on the left and billing and coding on the right, kept in sync. Confirm the E/M level 99213, CPT 11042 for debridement with a modifier-25 flag, and ICD-10 codes L97.419 and E11.621. 4. Run Ask Pingoo. The chart-auditor pass surfaces compliance, measurement, medication, and coding flags in plain language — a missing depth, modifier 25, or no offloading for a diabetic heel ulcer. Decision support offers next steps with CPT codes and approximate Medicare reimbursement. 5. Sign. WoundScribe runs a final compliance check. Amber gaps, like a missing measurement for 99213, are flagged but allow signing. Red payer-specific issues — Medicare wanting modifier 25 — must be resolved, with a one-click fix and a citation to the CMS NCCI Policy Manual. 6. Confirm and close. Approve the new diagnoses pulled from your SOAP Assessment, then sign. The encounter locks, but you can unlock deliberately for an addendum. Download the audit bundle — final notes, patient summary, revision trail, signatures, compliance results, and billing status — in one package. The result: every signed note is audit-ready by design. For more on coding accuracy, see AI wound coding and reimbursement.